Privacy for Personal Neuroinformatics

29 Pages Posted: 22 Apr 2014  

Arkadiusz Stopczynski

Technical University of Denmark

Dazza Greenwood

CIVICS.com Consultancy; Massachusetts Institute of Technology - MIT Media Lab

Lars Kai Hansen

Technical University of Denmark

Alex Pentland

Massachusetts Institute of Technology (MIT)

Date Written: April 21, 2014

Abstract

Human brain activity collected in the form of Electroencephalography (EEG), even with low number of sensors, is an extremely rich signal raising legal and policy issues. Traces collected from multiple channels and with high sampling rates capture many important aspects of participants' brain activity and can be used as a unique personal identifier. The motivation for sharing EEG signals is significant, as a mean to understand the relation between brain activity and well-being, or for communication with medical services. As the equipment for such data collection becomes more available and widely used, the opportunities for using the data are growing; at the same time however inherent privacy risks are mounting. The same raw EEG signal can be used for example to diagnose mental diseases, find traces of epilepsy, and decode personality traits. The current practice of the informed consent of the participants for the use of the data either prevents reuse of the raw signal or does not truly respect participants' right to privacy by reusing the same raw data for purposes much different than originally consented to. Here we propose an integration of a personal neuroinformatics system, Smartphone Brain Scanner, with a general privacy framework openPDS. We show how raw high-dimensionality data can be collected on a mobile device, uploaded to a server, and subsequently operated on and accessed by applications or researchers, without disclosing the raw signal. Those extracted features of the raw signal, called answers, are of significantly lower-dimensionality, and provide the full utility of the data in given context, without the risk of disclosing sensitive raw signal. Such architecture significantly mitigates a very serious privacy risk related to raw EEG recordings floating around and being used and reused for various purposes.

Keywords: legal, technical, business, neurological, privacy, policy, personal informatics

Suggested Citation

Stopczynski, Arkadiusz and Greenwood, Dazza and Hansen, Lars Kai and Pentland, Alex, Privacy for Personal Neuroinformatics (April 21, 2014). Available at SSRN: https://ssrn.com/abstract=2427564 or http://dx.doi.org/10.2139/ssrn.2427564

Arkadiusz Stopczynski

Technical University of Denmark ( email )

Anker Engelunds Vej 1
Building 101A
Lyngby, 2800
Denmark

Dazza Greenwood (Contact Author)

CIVICS.com Consultancy ( email )

PO BOX 425845
Cambridge, MA 02142
United States
617-500-3644 (Phone)

HOME PAGE: http://dazzagreenwood.com

Massachusetts Institute of Technology - MIT Media Lab ( email )

77 Massachusetts Avenue
Room E15-384B
Cambridge, MA 02139
United States
617-500-3644 (Phone)

HOME PAGE: http://hd.media.mit.edu

Lars Kai Hansen

Technical University of Denmark ( email )

Anker Engelunds Vej 1
Building 101A
Lyngby, 2800
Denmark

Alex Pentland

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

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